prompt-engineering

SKILL.md

Advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability.

Teach the model by showing examples instead of explaining rules. Include 2-5 input-output pairs that demonstrate the desired behavior. Use when you need consistent formatting, specific reasoning patterns, or handling of edge cases. More examples improve accuracy but consume tokens—balance based on task complexity.

Request step-by-step reasoning before the final answer. Add "Let's think step by step" (zero-shot) or include example reasoning traces (few-shot). Use for complex problems requiring multi-step logic, mathematical reasoning, or when you need to verify the model's thought process. Improves accuracy on analytical tasks by 30-50%.

有关即时工程模式、最佳实践和优化技术的专家指南。当用户想要改进提示、学习提示策略或调试代理行为时使用。 来源：poletron/custom-rules。

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